PLENARY TALKS

Abstract

This talk will discuss recent developments in the use of digital tools such as interactive simulations, online platforms, digital makerspaces and serious games in the Education 4.0 paradigm in teaching and learning mathematics. When educators effectively leverage these tools, they can promote 21st century skills such as creativity, problem-solving,  critical thinking, communication, and collaboration.

Methods on how teachers integrate AI to develop (rather than hamper) problem solving and critical thinking skills among students will  be discussed. Data and findings from the literature on the benefits and challenges of using digital tools and AI in mathematics teaching and learning will be presented.

In the last part of the talk, the audience will be introduced to the  development and research design of Biringan,  a first serious game in Calculus, that is set in the Philippines.

About the Speaker

Ma. Louise Antonette N. De Las Peñas is a Professor of Mathematics based at the Department of Mathematics, Ateneo de Manila University (ADMU). A mathematician and prolific researcher, she is recognized for her expertise in Discrete Geometry and Mathematical Crystallography, and Technology in Mathematics Education. Prof. De Las Peñas is a recipient of several research awards including the National Research Council of the Philippines (NRCP) Achievement Award in the Mathematical Sciences and the Commission on Higher Education (CHED) Republica National Research Award. She has published her research extensively in over one hundred publications including at least sixty six (66) Scopus/Web of Science indexed journals, book chapters and international conference publications. At present, Prof. De Las Peñas is President and Chair of the Mathematical Sciences Division of the NRCP, and member of the CHED Technical Panel in Mathematics. She is member of the International Union of Crystallography Commission in Mathematical Crystallography and the International Program Committee of the Asian Technology Conference in Mathematics. She is currently Co-Editor of Acta Crystallographica A , Column Editor of the Mathematical Tourist of the Mathematical Intelligencer and Editor of the Electronic Journal of Mathematics and Technology.

Abstract

An intelligent system uses state-of-the-art computational techniques to solve complex problems by processing data, learning from it, making decisions, and adapting to new inputs. We show how applied mathematics can be a collaborative link between real-world challenges and their solutions through intelligent systems. This talk examines computational approaches with an emphasis on numerical algorithms, optimization techniques, and their applications. Examples will be provided from optical character recognition of Baybayin texts, inverse problems in cosmology, optimal control for infectious disease modeling, and machine learning for image reconstruction, to demonstrate how scientific computing connects theory and data to promote intelligent decision-making across multiple domains.

About the Speaker

Dr. Renier Mendoza is an Associate Professor at the Institute of Mathematics, University of the Philippines Diliman. He heads the Numerical Analysis and Scientific Computing Academic Group and serves as the Program Director of the Computational Science Research Center. Additionally, he is the Coordinator of the College of Science Data Science Graduate Program.

Dr. Mendoza earned his BS in Mathematics and MS in Applied Mathematics from UP Diliman and completed his doctoral studies in Mathematics at Karl-Franzens University of Graz, Austria. He was a postdoctoral researcher at the Department of Mathematics, Konkuk University, Seoul, South Korea.

Dr. Mendoza's research covers various areas of applied mathematics, including inverse problems, numerical optimization, numerical analysis, mathematical modeling, and data science.

Dr. Mendoza received three prestigious awards from the National Academy of Science and Technology (NAST) for his scientific contributions:  the 2024 Outstanding Young Scientist Award in Mathematics, the 2021 Grand Prize in the Talent Search for Young Scientists, and a 2024 Outstanding Scientific Paper Award for a research work on Baybayin Optical Character Recognition.

Abstract

Youngs proved that every non-bipartite quadrangulation of the projective plane is 4-chromatic. Hachimori et al. defined a high-dimensional quadrangulation, called a normal quadrangulation and proved that if a non-bipartite normal quadrangulation G of the d-dimensional projective space satisfies a certain geometric condition, then G is 4-chromatic. They also asked whether the geometric condition can be removed from the result. In this talk, we give a negative solution to their problem for the 3-dimensional case, proving that there exist normal quadrangulations of the 3-dimensional projective space whose chromatic number is arbitrarily large. Moreover, we prove that no normal quadrangulations of the d-dimensional projective space has chromatic number 3.

This is a joint work with Tomas Kaiser (University of West Bohemia in Pilsen, Czech Republic), On-Hei Solomon Lo (Tongji University, China), Atsuhiro Nakamoto (Yokohama National University, Japan) and Yuta Nozaki (Yokohama National University and Hiroshima University, Japan).

About the Speaker

Kenta Ozeki earned his Ph.D. from Keio University, Yokohama, Japan in 2009. He then briefly served as a research fellow in the same university and then at National Institute of Informatics, Tokyo, Japan, where he also became project assistant professor until 2017. Shortly afterwards, he joined Yokohama National University, where he is now a professor. In 2023, Prof. Ozeki was awarded the prestigious Hall Medal of the Institute of Combinatorics and its Applications for his "deep contributions in structural and topological graph theory." He also serves as editor for a number of mathematics journals including Graphs and Combinatorics and the Journal of Algebra Combinatorics Discrete Structures and Applications.

Abstract

While mathematical modeling necessitates a strong foundation in both mathematical and programming skills, developing models that can effectively produce substantial real-world impacts on a large scale requires additional considerations. Building successful partnerships involves a thoughtful approach, including the identification of shared objectives, the establishment of trust, and the optimization of synergy and diversity—all of which demand significant investment of time. As a researcher, engaging in collaborative partnerships early in one's career can prove to be highly advantageous. In this presentation, we will explore the process of cultivating relationships with various partners from initial engagement to navigating the challenges associated with non-modeling aspects of collaboration. I will also share insights from real case studies based on my experiences.

About the Speaker

Wirichada is a mathematical modeller based in Bangkok, Thailand. Her main research areas are neglected tropical and zoonotic diseases. She is enthusiastic to use mathematical and economic modelling to help find solutions to health issues regionally, in particular when it can serve as a tool for guiding policy decisions. In addition, she is keen to strengthen the modelling networks in Southeast Asia where the communities are relatively small, and to expand research collaboration in the global south.

Website: https://www.tropmedres.ac/team/wirichada-pan-ngum

Abstract

Integer-valued time series data commonly arise across various fields, including finance, health sciences, medicine, environmental studies, and epidemiology. This talk presents a class of integer-valued time series models developed to address several key challenges: overdispersion, zero inflation, the presence of outliers or structural interventions, and the incorporation of exogenous variables. To estimate the unknown parameters and perform model selection among competing alternatives, we employ Adaptive Markov Chain Monte Carlo (MCMC) techniques. To assess the performance of the proposed methods, we conduct a simulation study and results demonstrate that the adaptive MCMC approach yields accurate and reliable parameter estimates. We also present an empirical analysis using real-world datasets, including crime statistics and dengue incidence data. For the crime dataset, the model successfully detects the locations and types of interventions. In the case of dengue incidence, the results confirm the model’s ability to capture both overdispersion and zero inflation inherent in the data.

About the Speaker

Dr. Aljo Clair P. Pingal is an Associate Professor at the Department of Mathematics and Statistics, College of Science and Mathematics, Mindanao State University – Iligan Institute of Technology (MSU-IIT), where he has served since 2011. He holds a PhD in Applied Statistics from Feng Chia University, Taiwan, specializing in Bayesian modeling of integer-valued transfer function models. His scholarly work lies at the intersection of Bayesian analysis, time series modeling, and biostatistics, with significant contributions in sequential estimation and spatio-temporal forecasting of epidemiological data.

Dr. Pingal is a multi-awarded academic, having received the 2nd Prize in the C.Z. Wei Memorial Award for Best Dissertation from the Chinese Institute of Probability and Statistics (2022). His excellence in research has also been recognized with Best Paper Presenter and Best Poster Awards in regional and institutional research symposia. His publications span international journals including Statistical Modelling and Statistics and Probability Letters, and he is actively engaged in collaborative and interdisciplinary research on advanced count data modeling for public health and environmental studies.

He currently serves as an Executive Committee Member of the International Society for Business and Industrial Statistics (ISBIS) and is affiliated with the International Society for Bayesian Analysis (ISBA) and the Mathematical Society of the Philippines. Dr. Pingal has also played a key role in mentoring emerging scholars and leads ongoing projects focused on adaptive MCMC-based spatio-temporal modeling and Bayesian applications in tropical disease surveillance.

Abstract

We consider a domain Ωa ⊆ R2 with ramified boundary Γ∞a, for a a parameter with 1/2 ≤ a ≤ a∗ ≃ 0.593465. This domain represents an idealization of bronchial trees in the lungs system. Since the exchanges between the lungs and the circulatory system take place only in the last generation of the bronchial trees, an accurate model for diffusion of oxygen may involve inhomogeneous Robin boundary conditions over Γ∞a. Therefore, we investigate the realization of the diffusion equation

∂u/∂t - Au + αu = f(x,t) in Ωa × (0,∞)

with mixed boundary conditions

∂u/∂νA + βu = g(x,t) on Γ∞a × (0,∞); u = 0 in (∂Ωa \ Γ∞a) × (0,∞),

and u(x,0) = u0 ∈ C(bar(Ωa)), where A stands as a linear (possibly non-symmetric) divergence-type differential operator, ∂u/∂nuA represents a generalized notion of a normal derivative over irregular surfaces, α ∈ Lr(Ωa), β ∈ Lsμ(Γ∞a)+ with ess inf {x∈Γ∞a : |β(x)| ≥ β0} for some constant β0 > 0 large enough, where min{r,s} > 1. We show unique solvability of this diffusion equation, and moreover we establish that weak solution of this model equation are globally continuous in space and in time.

About the Speaker

Alejandro Vélez-Santiago was born in San Juan, Puerto Rico, and is the third son of a family of six siblings. His life story is one full of challenges, but also of hope and miracles. He was born with two major conditions: autism and chronic asthma. Alejandro liked math and music since he was a kid, and his parents put him in violin classes at the age of 10 years. From there, Alejandro excelled in music, particularly in violin performance, and began to play violin with the Puerto Rico Symphony Orchestra when he was in 11th grade in high school. During that period Alejandro also experienced a great miracle: when he was 16 years old the Lord healed him from both his autism, and his condition of chronic asthma. Alejandro was a product of homeschooling, which he considers to be a special part of his life. Since he was so advanced in violin performance, he first wanted to pursue his career as a violinist, but after following the advice of his parents, he also completed a bachelor’s degree in Mathematics (2004) at the University of Puerto Rico – Río Piedras (UPRRP), and then completed his Ph.D. in Mathematics (2010) at the same institution. After two postdoctoral positions (2010-2011 at Iowa State University and 2013-2016 at the University of California Riverside), he was hired by the University of Puerto Rico – Mayagüez (UPRM), where he worked until 2023. At Fall 2023, he transferred to the University of Puerto Rico – Río Piedras (UPRRP), where he currently is an Associate Professor of Mathematics. Alejandro is very thankful to many who have influenced his life, especially to his parents and family for their love, sacrifice, and teachings. But among all, he is very thankful to the Lord Jesus Christ for healing him, loving him, and being with him during all the steps in his life.

Alejandro’s research lies in the combination of Analysis, Partial Differential Equations (PDEs), Measure Theory, Potential Theory, Operator Theory, and Fractal Geometry (among others). His primary research consists of the solvability and regularity theory of various boundary value problems over non-smooth regions, which at times include domains with fractal boundaries and rough-type domains. Alejandro has also investigated models of quasi-linear-type boundary value problems exhibiting a nonstandard growth structure, which is a consequence of the presence of variable exponent function spaces and PDEs, and also of double-phase structure. Alejandro loves to involve students (at both the undergraduate and graduate level) into his research projects. He has conducted undergraduate research with multiple undergraduate students and has mentored eight graduate students who did their master’s thesis under his mentorship. Alejandro loves to help his graduate students as much as possible with gaining quality research experiences in order to increase their opportunities of success in the future after graduation. This is why he has published (or submitted) an original research paper with each of his graduate students and strives to publish a research article with every graduate student he works with. He has also been able to publish research papers with his undergraduate students.